Conversational AI - Towards a New Era of Interactive Intelligence
Dinesh Chandrasekar, VP- Solution Engineering & Platform Innovation, Pactera Technologies India Pvt Ltd
When things go digital, they set a new path of rules. When it comes to Technology what does the future hold for us? This is the question we repeatedly ask ourselves and most of us are keen to make our contributions to this constant technology revolution but what is that one thing that is changing the future for us? It is AI-Artificial Intelligence. Back in the 1950s, the fathers of the field Minsky and McCarthy, described artificial intelligence as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task. AI today is in brief, a specific area of computer science that aims to create machines able not only to work and think, but also to act and react, as we, human beings, would. Conversational AI agents are becoming game changers in many industries specially the ones which are driven by customer experience.
Conversational AI is an AI enabled human like agent/ assistant that can help smoothen your Customer/Employee interaction with its unique Cognitive abilities to solve issues based on an interactive framework and knowledge base. With a Unique Product Roadmap and Architecture Conversational AI agents have been giving top notch services to global retail, F&B, industrial, Pharma companies etc. The Conversational AI can integrate itself to various channels for interaction such as Facebook, Skype, WeChat, SMS, Cortana etc. For users, conversational AI offers for the first time a means to interact with technology using their own words. For enterprises conversational AI offers not just a chance to differentiate themselves in a crowded marketspace, but the opportunity to garner valuable data on the voice of customer.
Conversational AI is based on a Machine learning algorithm model that learns the actions based on the training data provided (unlike a traditional state machine based architecture that is based on coding all the possible if else conditions for each possible state of the conversation). As the picture above suggest there is a module framework with various components into use while developing a Conversational AI. The C-AI is built on a SDK - The Bot Builder SDK (A software development kit) which is an easy-to-use framework for developing bots using Visual Studio and Windows (or other sources). The Framework allows you to create bot applications which can respond to natural language input from end users, in the places where they are already having conversations. This can be places like Facebook, Skype, Slack and even SMS/text. The Bot Connector lets you connect your bot(s) seamlessly to text/sms, Office 365 mail, Skype, Slack, and other services. Simply register your bot, configure desired channels and publish in the Bot Directory.
Bot coding inputs are needed in the module managements that helps build the C-AI. NLU (Natural Language Understanding) component constitutes a supervised intent classification model that is trained on varieties of sentences as input and intents as target. Conversion of spoken audio to text or text to audio with default or custom models tailored to specific vocabulary or speaking styles of users using Speech to Text (Text to Speech) Translation and transcription services is an integral part of Conversational AI. Language Understanding integrates seamlessly with the Speech service for instant Speech to Intent processing. Powerful developer tools are combined with customisable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly. Smarter AI agents can be built through Emotion API (application program interface) that can detect facial expressions, user moods and respond accordingly. Using the Knowledge API requires a certain level of skills that the module development candidate can acquire by reading the API documentation. There are several API documentation entry points, each of them corresponding to a particular level of abstraction and details final output: The conversational Flow between the customer and Bot through the various Interaction Channels.
With Conversational AIs Businesses can: -
• Leverage their unique data and augment the business in new, unimaginable ways.
• Interpret business and customer data in real time and scale including text, docs, images-OCR (Optical Character Recognition), video, and voiceprint.
• Remove technology barriers with customers and multiply employee capabilities.
• Increase sales across digital commerce channels with personalized, 24x7 human-like ‘bots’.
• Lower costs of customer service, and improve customer satisfaction and loyalty.
• Increase employee productivity and satisfaction by automating high frequency and routine service desk interactions.
Integration with external systems is key for improving business agility, increasing personalization and customer satisfaction. As the use of AI in businesses develops it will be essential for information and data assets to be shared across the enterprise. This is quite possible given how AI-driven every technology is aspiring to transform itself into. The future will be made easy for Humans as conversational AI might just handle business operations for us or at least become an integral part everywhere. The AI omnipresence is what that will change the future!